Endoscopic image analysis using Deep Convolutional GAN and traditional data

One big challenge encountered in the medical field is the availability of only limited annotated datasets for research. On the other hand, medical image annotation requires a lot of input from medical experts. It is noticed that machine learning and deep learning are producing better results in the area of image classification. However, these techniques require large training datasets, which is the major concern for medical image processing. Another issue is the unbalanced nature of the different classes of data, leading to the under-representation of some classes. Data augmentation has emerged as a good technique to deal with these challenges. In this work, we have applied traditional data augmentation and Generative Adversarial Network (GAN) on endoscopic esophagus images to increase the number of images for the training datasets. Eventually we have applied two deep learning models namely ResNet50 and VGG16 to extract and represent the relevant cancer features. The results show that the accuracy of the model increases with data augmentation and GAN. In fact, GAN has achieved the highest accuracy, that is, 94% over non-augmented training set and traditional data augmentation for VGG16

Prospects for the Improvement of Energy Performance in Agroindustry Using Phase Change Materials

This work was partially supported by the Fundação para a Ciência e Tecnologia, UIDB/00066/2020 (CTS – Center of Technology and Systems).The use of Phase Change Materials (PCMs), able to store latent heat, represents an opportunity to improve energy efficiency in the agroindustry by means of thermal energy storage. PCMs provide higher energy density then sensible heat storage mediums, thus paving the way to multiple applications, like supporting the integration of renewables or allowing for new storage architectures, decentralized and directly installed in the chain production equipment, creating e.g. the opportunity to recover and value low-grade operational heat sub-products. Such new and decentralized architecture, not currently applied in agroindustry, is proposed in this work. A chocolate tempering machine using an organic PCM is conceived and analyzed using ANSYS Fluent software for computational fluid dynamics simulations, comparing the main aspects in the storage capacity and discharging process with a conventional sensitive heat storage solution that uses water. PCMs allows improving the stored energy, keeping the chocolate in the working temperature after being tempered for more than four times longer than using only hot water. If the PCMs are charged by renewables, the self-consumption ratio can be improved while providing energy flexibility to the user.authorsversionpublishe

A Putative P-Type ATPase Required for Virulence and Resistance to Haem Toxicity in Listeria monocytogenes

Regulation of iron homeostasis in many pathogens is principally mediated by the ferric uptake regulator, Fur. Since acquisition of iron from the host is essential for the intracellular pathogen Listeria monocytogenes, we predicted the existence of Fur-regulated systems that support infection. We examined the contribution of nine Fur-regulated loci to the pathogenicity of L. monocytogenes in a murine model of infection. While mutating the majority of the genes failed to affect virulence, three mutants exhibited a significantly compromised virulence potential. Most striking was the role of the membrane protein we designate FrvA (Fur regulated virulence factor A; encoded by frvA [lmo0641]), which is absolutely required for the systemic phase of infection in mice and also for virulence in an alternative infection model, the Wax Moth Galleria mellonella. Further analysis of the ΔfrvA mutant revealed poor growth in iron deficient media and inhibition of growth by micromolar concentrations of haem or haemoglobin, a phenotype which may contribute to the attenuated growth of this mutant during infection. Uptake studies indicated that the ΔfrvA mutant is unaffected in the uptake of ferric citrate but demonstrates a significant increase in uptake of haem and haemin. The data suggest a potential role for FrvA as a haem exporter that functions, at least in part, to protect the cell against the potential toxicity of free haem

Comparative Transcriptional Profiling of Bacillus cereus Sensu Lato Strains during Growth in CO2-Bicarbonate and Aerobic Atmospheres

Bacillus species are spore-forming bacteria that are ubiquitous in the environment and display a range of virulent and avirulent phenotypes. This range is particularly evident in the Bacillus cereus sensu lato group; where closely related strains cause anthrax, food-borne illnesses, and pneumonia, but can also be non-pathogenic. Although much of this phenotypic range can be attributed to the presence or absence of a few key virulence factors, there are other virulence-associated loci that are conserved throughout the B. cereus group, and we hypothesized that these genes may be regulated differently in pathogenic and non-pathogenic strains.Here we report transcriptional profiles of three closely related but phenotypically unique members of the Bacillus cereus group--a pneumonia-causing B. cereus strain (G9241), an attenuated strain of B. anthracis (Sterne 34F(2)), and an avirulent B. cereus strain (10987)--during exponential growth in two distinct atmospheric environments: 14% CO(2)/bicarbonate and ambient air. We show that the disease-causing Bacillus strains undergo more distinctive transcriptional changes between the two environments, and that the expression of plasmid-encoded virulence genes was increased exclusively in the CO(2) environment. We observed a core of conserved metabolic genes that were differentially expressed in all three strains in both conditions. Additionally, the expression profiles of putative virulence genes in G9241 suggest that this strain, unlike Bacillus anthracis, may regulate gene expression with both PlcR and AtxA transcriptional regulators, each acting in a different environment.We have shown that homologous and even identical genes within the genomes of three closely related members of the B. cereus sensu lato group are in some instances regulated very differently, and that these differences can have important implications for virulence. This study provides insights into the evolution of the B. cereus group, and highlights the importance of looking beyond differences in gene content in comparative genomics studies

BosR (BB0647) Controls the RpoN-RpoS Regulatory Pathway and Virulence Expression in Borrelia burgdorferi by a Novel DNA-Binding Mechanism

In Borrelia burgdorferi (Bb), the Lyme disease spirochete, the alternative σ factor σ54 (RpoN) directly activates transcription of another alternative σ factor, σS (RpoS) which, in turn, controls the expression of virulence-associated membrane lipoproteins. As is customary in σ54-dependent gene control, a putative NtrC-like enhancer-binding protein, Rrp2, is required to activate the RpoN-RpoS pathway. However, recently it was found that rpoS transcription in Bb also requires another regulator, BosR, which was previously designated as a Fur or PerR homolog. Given this unexpected requirement for a second activator to promote σ54-dependent gene transcription, and the fact that regulatory mechanisms among similar species of pathogenic bacteria can be strain-specific, we sought to confirm the regulatory role of BosR in a second virulent strain (strain 297) of Bb. Indeed, BosR displayed the same influence over lipoprotein expression and mammalian infectivity for strain Bb 297 that were previously noted for Bb strain B31. We subsequently found that recombinant BosR (rBosR) bound to the rpoS gene at three distinct sites, and that binding occurred despite the absence of consensus Fur or Per boxes. This led to the identification of a novel direct repeat sequence (TAAATTAAAT) critical for rBosR binding in vitro. Mutations in the repeat sequence markedly inhibited or abolished rBosR binding. Taken together, our studies provide new mechanistic insights into how BosR likely acts directly on rpoS as a positive transcriptional activator. Additional novelty is engendered by the facts that, although BosR is a Fur or PerR homolog and it contains zinc (like Fur and PerR), it has other unique features that clearly set it apart from these other regulators. Our findings also have broader implications regarding a previously unappreciated layer of control that can be involved in σ54–dependent gene regulation in bacteria

Comparative Transcriptome Analysis of Bacillus subtilis Responding to Dissolved Oxygen in Adenosine Fermentation

Dissolved oxygen (DO) is an important factor for adenosine fermentation. Our previous experiments have shown that low oxygen supply in the growth period was optimal for high adenosine yield. Herein, to better understand the link between oxygen supply and adenosine productivity in B. subtilis (ATCC21616), we sought to systematically explore the effect of DO on genetic regulation and metabolism through transcriptome analysis. The microarrays representing 4,106 genes were used to study temporal transcript profiles of B. subtilis fermentation in response to high oxygen supply (agitation 700 r/min) and low oxygen supply (agitation 450 r/min). The transcriptome data analysis revealed that low oxygen supply has three major effects on metabolism: enhance carbon metabolism (glucose metabolism, pyruvate metabolism and carbon overflow), inhibit degradation of nitrogen sources (glutamate family amino acids and xanthine) and purine synthesis. Inhibition of xanthine degradation was the reason that low oxygen supply enhanced adenosine production. These provide us with potential targets, which can be modified to achieve higher adenosine yield. Expression of genes involved in energy, cell type differentiation, protein synthesis was also influenced by oxygen supply. These results provided new insights into the relationship between oxygen supply and metabolism

A reexamination of information theory-based methods for DNA-binding site identification

<p>Abstract</p> <p>Background</p> <p>Searching for transcription factor binding sites in genome sequences is still an open problem in bioinformatics. Despite substantial progress, search methods based on information theory remain a standard in the field, even though the full validity of their underlying assumptions has only been tested in artificial settings. Here we use newly available data on transcription factors from different bacterial genomes to make a more thorough assessment of information theory-based search methods.</p> <p>Results</p> <p>Our results reveal that conventional benchmarking against artificial sequence data leads frequently to overestimation of search efficiency. In addition, we find that sequence information by itself is often inadequate and therefore must be complemented by other cues, such as curvature, in real genomes. Furthermore, results on skewed genomes show that methods integrating skew information, such as <it>Relative Entropy</it>, are not effective because their assumptions may not hold in real genomes. The evidence suggests that binding sites tend to evolve towards genomic skew, rather than against it, and to maintain their information content through increased conservation. Based on these results, we identify several misconceptions on information theory as applied to binding sites, such as negative entropy, and we propose a revised paradigm to explain the observed results.</p> <p>Conclusion</p> <p>We conclude that, among information theory-based methods, the most unassuming search methods perform, on average, better than any other alternatives, since heuristic corrections to these methods are prone to fail when working on real data. A reexamination of information content in binding sites reveals that information content is a compound measure of search and binding affinity requirements, a fact that has important repercussions for our understanding of binding site evolution.</p

Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa

Background Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa. Results Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608–0.707, OR 2.37–5.71) than for African individuals (AUC 0.502–0.585, OR 0.95–2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores. Conclusions Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities